bims-ovdlit Biomed News
on Ovarian cancer: early diagnosis, liquid biopsy and therapy
Issue of 2021‒10‒17
three papers selected by
Lara Paracchini
Humanitas Research

  1. JAMA Oncol. 2021 Oct 14.
      Importance: A total of 1% to 3% of patients treated with a poly(adenosine diphosphate-ribose) polymerase inhibitor for high-grade ovarian cancer (HGOC) develop therapy-related myeloid neoplasms (t-MNs), which are rare but often fatal conditions. Although the cause of these t-MNs is unknown, clonal hematopoiesis of indeterminate potential (CHIP) variants can increase the risk of primary myeloid malignant neoplasms and are more frequent among patients with solid tumors.Objectives: To examine whether preexisting CHIP variants are associated with the development of t-MNs after rucaparib treatment and how these CHIP variants are affected by treatment.
    Design, Setting, and Participants: This retrospective genetic association study used peripheral blood cell (PBC) samples collected before rucaparib treatment from patients in the multicenter, single-arm ARIEL2 (Study of Rucaparib in Patients With Platinum-Sensitive, Relapsed, High-Grade Epithelial Ovarian, Fallopian Tube, or Primary Peritoneal Cancer) (n = 491; between October 30, 2013, and August 9, 2016) and the multicenter, placebo-controlled, double-blind ARIEL3 (Study of Rucaparib as Switch Maintenance Following Platinum-Based Chemotherapy in Patients With Platinum-Sensitive, High-Grade Serous or Endometrioid Epithelial Ovarian, Primary Peritoneal or Fallopian Tube Cancer) (n = 561; between April 7, 2014, and July 19, 2016), which tested rucaparib as HGOC therapy in the treatment and maintenance settings, respectively. The follow-up data cutoff date was September 1, 2019. Of 1052 patients in ARIEL2 and ARIEL3, PBC samples from 20 patients who developed t-MNs (cases) and 44 randomly selected patients who did not (controls) were analyzed for the presence of CHIP variants using targeted next-generation sequencing. Additional longitudinal analysis was performed on available ARIEL2 samples collected during treatment and at the end of treatment.
    Main Outcomes and Measures: Enrichment analysis of preexisting variants in 10 predefined CHIP-associated genes in cases relative to controls; association with clinical correlates.
    Results: Among 1052 patients (mean [SE] age, 61.7 [0.3] years) enrolled and dosed in ARIEL2 and ARIEL3, 22 (2.1%) developed t-MNs. The t-MNs were associated with longer overall exposure to prior platinum therapies (13.2 vs 9.0 months in ARIEL2, P = .04; 12.4 vs 9.6 months in ARIEL3, P = .003). The presence of homologous recombination repair gene variants in the tumor, either germline or somatic, was associated with increased prevalence of t-MNs (15 [4.1%] of 369 patients with HGOC associated with an HRR gene variant vs 7 [1.0%] of 683 patients with wild-type HGOC, P = .002). The prevalence of preexisting CHIP variants in TP53 but not other CHIP-associated genes at a variant allele frequency of 1% or greater was significantly higher in PBCs from cases vs controls (9 [45.0%] of 20 cases vs 6 [13.6%] of 44 controls, P = .009). TP53 CHIP was associated with longer prior exposure to platinum (mean 14.0 months of 15 TP53 CHIP cases vs 11.1 months of 49 non-TP53 CHIP cases; P = .02). Longitudinal analysis showed that preexisting TP53 CHIP variants expanded in patients who developed t-MNs.
    Conclusions and Relevance: The findings of this genetic association study suggest that preexisting TP53 CHIP variants may be associated with t-MNs after rucaparib treatment.
  2. Front Oncol. 2021 ;11 745808
      Ovarian cancer ranks as the fifth most common cause of cancer-related death in females. The molecular mechanisms of ovarian carcinogenesis need to be explored in order to identify effective clinical therapies for ovarian cancer. Recently, multi-omics approaches have been applied to determine the mechanisms of ovarian oncogenesis at genomics (DNA), transcriptomics (RNA), proteomics (proteins), and metabolomics (metabolites) levels. Multi-omics approaches can identify some diagnostic and prognostic biomarkers and therapeutic targets for ovarian cancer, and these molecular signatures are beneficial for clarifying the development and progression of ovarian cancer. Moreover, the discovery of molecular signatures and targeted therapy strategies could noticeably improve the prognosis of ovarian cancer patients.
    Keywords:  genomics; metabolomics; multi-omics; ovarian cancer; proteomics; systems biology; transcriptomics
  3. Nat Rev Clin Oncol. 2021 Oct 12.
      Accumulating evidence suggests that a high tumour burden has a negative effect on anticancer immunity. The concept of tumour burden, simply defined as the total amount of cancer in the body, in contrast to molecular tumour burden, is often poorly understood by the wider medical community; nonetheless, a possible role exists in defining the optimal treatment strategy for many patients. Historically, tumour burden has been assessed using imaging. In particular, CT scans have been used to evaluate both the number and size of metastases as well as the number of organs involved. These methods are now often complemented by metabolic tumour burden, measured using the more recently developed 2-deoxy-2-[18F]-fluoro-D-glucose (FDG)-PET/CT. Serum-based biomarkers, such as lactate dehydrogenase, can also reflect tumour burden and are often also correlated with a poor response to immune-checkpoint inhibitors. Other circulating markers (such as circulating free tumour DNA and/or circulating tumour cells) are also attracting research interest as surrogate markers of tumour burden. In this Review, we summarize evidence supporting the utility of tumour burden as a biomarker to guide the use of immune-checkpoint inhibitors. We also describe data and provide perspective on the various tools used for tumour burden assessment, with a particular emphasis on future therapeutic strategies that might address the issue of inferior outcomes among patients with cancer with a high tumour burden.